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3D Anomaly Detection

3D-only Anomaly Detection. Structures out of normal distribution are detected from the 3D-only point cloud.

Papers

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 11–20 of 36 papers

Title	Date	Tasks	Status	Hype
Towards Generic Anomaly Detection and Understanding: Large-scale Visual-linguistic Model (GPT-4V) Takes the Lead	Nov 5, 2023	3D Anomaly DetectionAnomaly Detection	CodeCode Available	1
Real3D-AD: A Dataset of Point Cloud Anomaly Detection	Sep 23, 2023	3D Anomaly DetectionAnomaly Detection	CodeCode Available	1
Shape-Guided: Shape-Guided Dual-Memory Learning for 3D Anomaly Detection	Jan 27, 2023	3D Anomaly Detection3D Anomaly Detection and Segmentation	CodeCode Available	1
Asymmetric Student-Teacher Networks for Industrial Anomaly Detection	Oct 14, 2022	3D Anomaly DetectionAnomaly Detection	CodeCode Available	1
Back to the Feature: Classical 3D Features are (Almost) All You Need for 3D Anomaly Detection	Mar 10, 2022	3D Anomaly Detection3D Anomaly Detection and Segmentation	CodeCode Available	1
Taming Anomalies with Down-Up Sampling Networks: Group Center Preserving Reconstruction for 3D Anomaly Detection	Jul 5, 2025	3D Anomaly DetectionAnomaly Detection	—Unverified	0
SiM3D: Single-instance Multiview Multimodal and Multisetup 3D Anomaly Detection Benchmark	Jun 26, 2025	3D Anomaly Detection3D Anomaly Detection and Segmentation	—Unverified	0
Bridging 3D Anomaly Localization and Repair via High-Quality Continuous Geometric Representation	May 30, 2025	3D Anomaly DetectionAnomaly Detection	CodeCode Available	0
Mentor3AD: Feature Reconstruction-based 3D Anomaly Detection via Multi-modality Mentor Learning	May 27, 2025	3D Anomaly DetectionAnomaly Detection	—Unverified	0
Examining the Source of Defects from a Mechanical Perspective for 3D Anomaly Detection	May 9, 2025	3D Anomaly Detection3D Anomaly Detection and Segmentation	CodeCode Available	0

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All datasets Real 3D-AD Anomaly-ShapeNet Anomaly-ShapeNet10

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	DUS-Net	Mean Performance of P. and O.	0.82	—	Unverified
2	MC4AD	Mean Performance of P. and O.	0.81	—	Unverified
3	ISMP	Mean Performance of P. and O.	0.8	—	Unverified
4	MC3D-AD	Mean Performance of P. and O.	0.78	—	Unverified
5	PASDF	Mean Performance of P. and O.	0.77	—	Unverified
6	PO3AD	Mean Performance of P. and O.	0.77	—	Unverified
7	Group3AD	Mean Performance of P. and O.	0.74	—	Unverified
8	PointAD	Mean Performance of P. and O.	0.74	—	Unverified
9	IMRNet	Mean Performance of P. and O.	0.73	—	Unverified
10	GLFM	Mean Performance of P. and O.	0.72	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	MC4AD	O-AUROC	0.91	—	Unverified
2	PASDF	O-AUROC	0.9	—	Unverified
3	MC3D-AD	O-AUROC	0.84	—	Unverified
4	PO3AD	O-AUROC	0.84	—	Unverified
5	DUS-Net	O-AUROC	0.8	—	Unverified
6	R3D-AD	O-AUROC	0.75	—	Unverified
7	ISMP	O-AUROC	0.71	—	Unverified
8	IMRNet	O-AUROC	0.66	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	MC4AD	O-AUROC	0.89	—	Unverified
2	PatchCore (FPFH)	O-AUROC	0.88	—	Unverified
3	BTF (FPFH)	O-AUROC	0.63	—	Unverified
4	M3DM	O-AUROC	0.57	—	Unverified
5	PatchCore (PointMAE)	O-AUROC	0.57	—	Unverified
6	Reg3D-AD	O-AUROC	0.53	—	Unverified
7	BTF (Raw)	O-AUROC	0.5	—	Unverified